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Trap configuration and spacing influences parameter estimates in spatial capture-recapture models.

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Spatial capture-recapture models estimate population size, but trap design matters. Clustered traps work well with low detection rates, but spacing relative to home range size is key for accurate black bear population estimates.

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Area of Science:

  • Ecology
  • Wildlife Biology
  • Population Dynamics

Background:

  • Spatial capture-recapture (SCR) models are increasingly used for population size estimation.
  • Limited research exists on how sampling design and trap configuration impact SCR parameter estimates.
  • SCR models improve upon non-spatial methods by incorporating spatial variation in detection probability.

Purpose of the Study:

  • To evaluate the influence of trap configuration and spacing on population size and spatial scale parameter (sigma) estimates.
  • To assess how detection probability and home range size affect these estimates.
  • To provide guidance on optimal sampling designs for SCR studies.

Main Methods:

  • Simulated black bear (Ursus americanus) populations and SCR data.
  • Varied detection probability, home range size, and trap configurations (regular, clustered, sequential relocation).
  • Explored effects of trap spacing and number of traps per cluster.

Main Results:

  • Clustered trap arrangements performed well with low detection rates and were easier to implement than sequential designs.
  • Performance differences between configurations decreased as home range size increased.
  • Optimal trap spacing should be no more than twice the spatial scale parameter (sigma).

Conclusions:

  • Trap configuration and spacing significantly influence SCR model accuracy and precision.
  • Sampling designs must consider study area size, individual movement, and home range size.
  • SCR models are robust to various sampling designs, but careful planning enhances parameter estimation.